Systems for communicating encoded speech at low bit rates commonly include quantizing a vector which represents the shape of the vocal tract for a speaker. Vectors consisting of ten Line Spectral Frequencies (LSFs) are commonly used to represent the vocal tract for each speech frame for the speaker. Commonly, each speech frame is from 10 to 40 ms of sampled speech. A problem with systems using techniques which substitute a codebook vector for a vector representing a speech sample is the excessive time required to search a vector quantizer (VQ) codebook. Typically, a vector including ten LSFs can be adequately characterized by a twenty-four bit VQ without sacrificing perceptual quality. However, another problem is determining which vector from the set of vectors in the VQ codebook represents the best perceptual model for a speech sample. For example, when a twenty-four bit VQ codebook is "searched", the search includes comparing a ten dimensional input vector which represents the speech sample with 2.sup.24 VQ codebook vectors.
Techniques such as Multi-stage and split VQ can reduce the time to search a VQ codebook. However, a problem with such techniques is that, while typically reducing the time to search a VQ codebook, the vector selected to represent the speech sample fails to be perceptually optimal. So, another problem with existing techniques is that they do not efficiently determine a vector from a VQ codebook which represents the best perceptual model for a speech sample.
Thus, what is needed is a system and method for communicating a perceptually encoded speech spectrum signal in a time efficient manner. What is also needed is a system and method which search a VQ codebook for a vector which perceptually models a speech signal. Also needed is a system and method which improve the speed for searching a VQ codebook. What is also needed is a system and method which efficiently determine a vector to perceptually model a speech signal.